word boundary- hypothesisation in hindi speech - Speech and ...

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ABSTRACT -1 CONTENTS INTRODUCTION TO WORD BOUNDARY HYPOTHESISATION 1.1 Word boundary hypothesisation problem 1.2 Issues in word boundary hypothesisation 1.3 Studies on word boundary hypothesisation for Hindi 1.4 Organisation of the Thesis chuptff 2 A REVIEW OF THE STUDIES ON WORD BOUNDARY HYPOTHESISATION 2.1 Introduction 2.2 Role of word boundaries in improving lexical analysis 2.3 Techniques for word boundary hypothesisation 2.3.1 Word boundary hypothesisation techniques based on the language knowledge 2.3.2 Word boundary hypothesisation techniques based on the lexical knowledge 2.3.3 Word boundary hypothesisation techniques based on the prosodic knowledge 2.3.4 Word boundary hypothesisation techniques based on the acoustic-phonetic knowledge 2.3.5 Word boundary hypothesisation techniques for Hindi 2.4 Summary and Conclusions
-3 SIGNIFICANCE OF WORD BOUNDARIES IN LEXICAL qNALYSIS 3.1 Introduction 3.2 Lexical analyser 33 Lexical analysis without word boundaries 3.3.1 Results of lexical analysis with exact matching 3.3.2 Results of lexical analysis with approximate matching 3.4 Lexical analysis with word boundaries 3.5 Comparison of the lexical analysis results 3.6 Lexical analysis with partial knowledge of word boundaries 3.7 Summary and Conclusions -4 WORD BOUNDARY CLUES BASED ON THE LANGUAGE KNOWLEDGE 58 4.1 Introduction 5 8 43 Language clues for word boundary hypothesisation 5 8 4.3 Issues in the application of language clues 4.3.1 Input for the studies on the performance of language clues 4.3.2 Measures for estimating the performance of language clues 65 4.4 Results of word boundary hypothesisation using language clues 4.4.1 Results of word boundary hypothesisation using language clues for correct input 4.4.2 Results of word boundary hypothesisation using language clues for incorrect input 4.4.3 Distribution of subsentences in the hypotheses produced by the language clues 76 4.5 Use of lexical constraints to improve the performance of language clues 68 68 70 78
Page 1 and 2: Dr. €3. YEGNANARAYANA Professor D
Page 3: ACKNOWLEDGEMENTS I thank my researc
Page 7 and 8: 6.6 Location of word boundaries fro
Page 9 and 10: ABSTRACT This thesis addresses the
Page 11 and 12: \ known. The lexical analyser can n
Page 13 and 14: alounddhelongtableheagsnoddedenunis
Page 15 and 16: word boundaries into a text with wo
Page 17 and 18: words. The idea is to spot symbol s
Page 19 and 20: F1 position at a vowel-consonant bo
Page 21 and 22: -a2 A REVIEW OF THE STUDIES ON, WOR
Page 23 and 24: 1. When a midclass representation w
Page 25 and 26: particular interest is the performa
Page 27 and 28: was found that at broadclass level,
Page 29 and 30: in speaking rate indicate phrase bo
Page 31 and 32: y an estimator function E from the
Page 33 and 34: studies, the following issues are i
Page 35 and 36: 2. The effect of word boundary info
Page 37: * This selection can be done in man
Page 40 and 41: me : me:ra: metra: na: me:ra: na:m
Page 42 and 43: No. of alternatives 0-10 10-100 100
Page 44 and 45: 3.3.2 Results of lexical analysk wi
Page 46 and 47: had to be restricted to the above r
Page 48 and 49: Match Sentence nunber cost 1 2 3 4
Page 50 and 51: Match Sentence nuher cost 1 2 3 4 5
Page 52 and 53: 6 10 Number of 10 a1 ternate word s
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lexlcal analysis Mismatch cost Fig.
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had all word boundaries, is plotted
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Watch Sentence number cost 1 2 3 4
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Time lor lexical analysis 0 1 2 3 4
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Match Sentence tunter cost 1 2 3 4
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Time lor lexical analysis 1 0 1 2 3
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speech recognition process. On the
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proposed clues are based on the obs
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Case Markers: Pronouns : ka:, ki:,
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form. The above Hindi text was corr
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that if there are some substitution
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These measures were defined as foll
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Case Conjunc- Pronouns Verb Aux . A
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- I-' X Error in input text X Error
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% Error Fig.4.4 Results of word bou
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% Error Fig.4.5 A comparison of the
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0 I 1 I 0 10 20 30 40 50 60 % Error
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60 4 0 No. of subsentences No. of s
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LC1: A Hindi word can end either in
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Fig.4.10 along with the results for
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oundaries spotted) against system s
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from other words, such as 'national
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dictionary contained nearly 30000 w
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Vowel sequences Consonant sequences
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VC' were considered. It can be obse
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percentage of incorrect hypotheses
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% Error in input text 0 10 20 30 40
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% Error Fig.5.1 Results of word bou
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hypotheses produced by the lexical
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transformed into other nonword-inte
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WB hyp. errors 300 - 200 - ( v+> 10
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number of incorrect hypotheses will
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I--- Correctness 60 8o lmprovement
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% Error in input text 10 20 30 40 5
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will be smaller and hence S and P(y
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word boundary is within the consona
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clues except for clues of types CV'
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Pauses in speech, though small in n
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Several studies on English speech s
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Speaker VB hypotheses at various th
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Speaker UF hypotheses at various th
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Speaker UF hypotheses at various th
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Fig.6.1 The plot of pitch frequency
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From the results, it can be seen th
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speakers, with the incorrect hypoth
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durational effects. One possible ex
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From these results, it can be seen
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shown that the prosodic features of
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chapter 7 WORD BOUNDARY CLUES BASED
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consonants. Thus one can consider o
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Speaker VB hypotheses(VB:&) at vari
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Speaker UF hypotheses(UF:UI) at var
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Speaker UB hypotheses(UB:B) at vari
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high speaking rates. This is also b
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vowels preceding word boundaries, i
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word-final vowels than word-interna
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8.1 Introduction PERFORMANCE OF WOR
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Match Sentence nunber, cost 1 2 3 4
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75 Reduction in the time for lexica
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The reduction in the lexical analys
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Hatch Sentence nuher cost 1 2 3 4 5
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Chapter 9 SUMMARY AND CONCLUSIONS I
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In the last study (described in cha
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the language and lexical clues are
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REFERENCES Baken R.J. and Daniloff
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Cutler A. and Butterfield S. (199lb
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Prakash M., Ramana Rao G,V., Chandr
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Zelenski R. and Class F. (1983), A
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